制作的文字排版动画效果插件

解决了学校传统照明控制系统的难题。以学校教室智能照明控制系统设计为例，提出将智能照明控制系统设计应用到学校各个场所中的合理化方案。 关键字：智能照明控制系统 绿色照明 楼宇智能化 -Solve the school of traditional lighting control system problems. School classrooms Intelligent lighting control system design as an example, the proposed intelligent lighting control system design applied to the various places of the school rationalization program. Keywords: Intelligent lighting control system intelligent building green lighting

说明：  Eureka-client是spring Cloud注册中心构建客户端所需的jar包(Eureka-client is the jar package required by the spring Cloud registry to build clients)

多功能信号波形生成与频谱分析仪，本人大学的毕业论文-Multi-function waveform signal generation and spectrum analyzer, My University thesis

说明：  加载在fluent中，求解水的相变，可以得到水蒸发或冷凝的情况。(The evaporation or condensation of water can be obtained by calculating the phase transition of water loaded in fluent.)

说明：  64位驱动读写 源码 文件 纯源码 可易语言调用(64-bit Driver Read-Write Source Files)

说明：  Downloads of the software peaked in 2013 with an average of just under 148,000 per day compared to less than 50,000 in Q2 2019.(It can also read and write a wide variety of other file formats, with particular attention to those from)

cai shu zi you xi Applet ban

ofdm的matlab仿真程序，对学习ofdm技术的人员来说比较实用-OFDM matlab simulation program of learning OFDM technology officer for more practical

大家在有些时候希望自己做的控件是半透明或透明的，就像半透明的窗体一样，我经过一段时间的查询，发现这个是可以实现，我们来看看它的实现以及带来的一些问题吧。-Sometimes you want to do is control translucent or transparent, translucent windows like, I spent some time in and found that this can be achieved, we look at it and the realization of some of the issues now.

说明：  针对使用传统分类器预测配变重过载会因为重过载样本率较低而带来的总正确率很高，重过载预测正确率却很低这一问题，将重抽样与随机森林理论引入分类模型中，构建重抽样-随机森林分类器对配变重过载进行预测。结果表明，新方法在预测配变日重过载类型、重过载开始与结束时间、重过载严重程度方面有较高的准确率。(For the problem of using the traditional classifier to predict the distribution of heavy overload, the total correct rate is high because of the low overload sample rate, and the accuracy of the heavy overload prediction is very low. The resampling and random forest theory are introduced into the classification model. In the construction, the re-sampling-random forest classifier is used to predict the heavy-duty overload. The results show that the new method has higher accuracy in predicting the type of daily variable overload, the start and end time of heavy overload, and the severity of heavy overload.)